Can recruiters tell if you used AI to write your resume?

No, not reliably. There is no tool a recruiter can run on your resume that tells them with confidence whether a machine wrote it. The best-known attempt was withdrawn by the company that built it. The detectors still on sale fail hardest against people writing in a second language.

That is the answer to the question people are actually asking. The more useful question is different, and this post gets to it: your application is now checked in a way that does not care who typed the sentences.

What an AI detector actually measures

A detector does not read your resume and recognise a machine. It measures perplexity, which is roughly how predictable your next word is. Predictable writing scores as machine-written. Varied writing scores as human.

That is a proxy, and it breaks in a way you can measure.

Researchers at Stanford ran seven widely used GPT detectors over 91 real TOEFL essays written by people, and over a set of essays written by US eighth graders. The detectors were near-perfect on the eighth graders. On the TOEFL essays the average false positive rate was 61.22%. All seven detectors agreed that 18 of the 91 human essays were AI-written. At least one detector flagged 89 of the 91.

Then the researchers ran the experiment backwards. They took the US eighth-grade essays, which are unambiguously human, and asked ChatGPT to simplify the word choice. The average false positive rate went from 5.19% to 56.65%.

Read those two numbers next to each other. The same human essays, the same detectors, one change: a smaller vocabulary. That is what is being flagged. Not authorship. Vocabulary range.

So a detector run on your resume is not asking whether you used AI. It is asking whether you write in plain, regular English. Plenty of people do, for reasons that have nothing to do with software. English is their second language. Or their fourth. Or they were told, correctly, that a resume should be plain.

The company with the best data switched its detector off

OpenAI released an AI Text Classifier in January 2023. It withdrew the tool on 20 July 2023 and left a one-line note: the classifier is no longer available due to its low rate of accuracy.

That is the organisation with the most direct knowledge of how its own model writes, and it could not build a reliable detector for its own output. Every detector still on the market is working with less.

What recruiters say they catch

Recruiters do report catching people. It is worth reading what they say they caught.

Greenhouse surveyed 4,136 people across the US, UK, Ireland and Germany in November 2025. It found that 74% of US job seekers use AI in their search, and that 65% of hiring managers had caught applicants using AI deceptively. The specific tactics named were reading from AI-generated scripts in interviews (32%), hidden prompt injections in resumes (22%), and deepfakes (18%).

None of those is "wrote a resume with AI". They are impersonation, concealment and a live-interview cheat. The survey is a vendor survey with a self-reported sample, so treat the exact percentages as directional. The shape of the list is the part that matters, and it is consistent: what gets caught is a lie, not a tool.

The hidden-text tactic in that list is the one people ask about most, and it fails for a mechanical reason worth knowing. We covered it separately in does white text on a resume work.

The industry is buying verification, not detection

Watch where the money goes. It is not going into prose detectors.

In June 2025 Greenhouse announced a partnership with CLEAR to add identity verification to its hiring product. A candidate confirms who they are with a government ID and a selfie. Greenhouse's own description of the surrounding product is fraud signals and identity, with matching that explicitly does not automate a hiring decision. The Gartner prediction quoted in that announcement is that up to 25% of job applicants could be fraudulent by 2028.

In the same Greenhouse survey, 39% of recruiters said they were running more in-person interviews to check that candidates are who they say they are.

Nobody is trying to work out whether ChatGPT phrased your third bullet. They are trying to work out whether you exist and whether the resume is yours.

The risk moved, and it moved somewhere you can control

Here is what all of that adds up to.

The old fear was a filter. Something scans the document, spots a machine, and throws it out before a person reads it. That is not what happens, in the same way that an applicant tracking system does not reject you for using the wrong font. We wrote about what an ATS genuinely reads in is my resume ATS friendly, and about the numbers vendors sell in what is an ATS score.

The new risk is slower and much more expensive. You get the interview. Someone asks about the line that says you cut processing time by 40%. You do not know where 40% came from, because you did not put it there. That conversation ends the process, and it ends it after both sides have spent real time.

An invented number does not fail at the detector. It fails in the room.

What to do instead

Four checks. None of them is about hiding your tools.

Source every figure. For each number on the page, name where it came from. A dashboard, an invoice, a report, a manager who told you. If you cannot name the source, take the number out. A specific claim you cannot support is worse than no claim.

Say the bullet out loud. If you cannot expand any line into thirty seconds of detail, the line is not yours yet. Either get the detail or cut the line.

Keep your own words. If a sentence uses a word you would never say, change it back. This is not about evading a detector. It is about not being caught flat in an interview by your own resume.

Do not use a humanizer. They optimise for a measurement that does not work. The Stanford study moved detector scores in both directions with word-choice edits alone. You would be paying a tool to game a broken instrument, and changing nothing that a person will actually test.

The general rule: use AI for structure and phrasing, never for facts. It can organise what you did. It cannot know what you did.

That distinction matters more when you are writing in a second language, since the detectors are worst at that case and the advice to "sound more natural" is usually advice to sound more American. Conventions differ by market too. Our guide to a Dutch CV in English covers one of them.

Where the tool fits

Rzume never invents a line for you. If a bullet is vague, it asks what happened, and it writes from your answer. If you skip the question, the gap stays visible in the output as a bracket rather than being filled with a plausible number:

Moved [how many accounts, and over how long?] off the legacy billing system, with no interruption to invoicing.

That bracket is the point. It tells you exactly what is missing, and it cannot be read back at you in an interview as a claim you did not make.

Before any of that, Rzume shows you the parse: what a machine pulled out of your file, field by field, and what it could not place. The parse and the full review are free and need no account. Upload your resume, or read what each plan includes first.

Sources

• Liang, Yuksekgonul, Mao, Wu and Zou, GPT detectors are biased against non-native English writers, arXiv:2304.02819, submitted 6 April 2023. Published in Patterns, Cell Press, July 2023. Seven detectors, 91 TOEFL essays, and the US eighth-grade essays from the ASAP dataset.
• OpenAI, New AI classifier for indicating AI-written text. Withdrawal note dated 20 July 2023, as reported by Search Engine Land, 25 July 2023.
• Greenhouse, 2025 AI in Hiring Report, 19 November 2025. 4,136 respondents across the US, UK, Ireland and Germany. A vendor survey with a disclosed sample and self-reported answers.
• CLEAR, CLEAR and Greenhouse announce partnership to enable candidate verification, 12 June 2025, including the quoted Gartner prediction for 2028.
• Greenhouse, Real Talent product page, and Auto-reject support documentation.
• HR Dive, By 2028, 1 in 4 candidate profiles will be fake, Gartner predicts, 8 August 2025, reporting a Gartner survey of 3,000 job candidates.

All accessed 3 September 2026.